Metabolic adaptation in epithelial ovarian cancer metastasis
Bibliographic record
Abstract
Epithelial ovarian cancer (EOC) is highly lethal due to its unique metastatic characteristics. EOC spheroids enter a non-proliferative state, with hypoxic cores and reduced oncogenic signaling, all of which contribute to tumour dormancy during metastasis. We investigated the metabolomic states of EOC cells progressing through the three steps to metastasis. Metabolomes of adherent, spheroid, and re-adherent cells were validated by isotopic metabolic flux analysis and mitochondrial functional assays to identify metabolic pathways that were previously unknown to promote EOC metastasis. Although spheroids were thought to exist in a dormant state, metabolomic analysis revealed an unexpected upregulation of energy production pathways in spheroids, accompanied by increased abundance of tricarboxylic acid (TCA) cycle and electron transport chain proteins. Tracing of 13C-labelled glucose and glutamine showed increased pyruvate carboxylation and decreased glutamine anaplerosis in spheroids. Increased reductive carboxylation suggests spheroids adjust redox homeostasis by shuttling cytosolic NADPH into mitochondria via isocitrate dehydrogenase. Indeed, we observed spheroids have increased respiratory capacity and mitochondrial ATP production. Relative to adherent cells, spheroids reduced serine consumption and metabolism, processes which were reversed upon spheroid re-adherence. The data reveal a distinct metabolism in EOC spheroids that enhances energy production by the mitochondria while maintaining a dormant state with respect to growth and proliferation. The findings advance our understanding of EOC metastasis and identify the TCA cycle and mitochondrional activity as novel targets to disrupt EOC metastasis, providing new approaches to treat advanced disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".